Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry

Rios, R., Miller, R. J. H., Manral, N., Sharir, T., Einstein, A. J., Fish, M. B., Ruddy, T. D., Kaufmann, P. A., Sinusas, A. J., Miller, E. J., Bateman, T. M., Dorbala, S., Di Carli, M., Van Kriekinge, S. D., Kavanagh, P. B., Parekh, T., Liang, J. X., Dey, D., Berman, D. S., & Slomka, P. J. (2022). Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry. Computers in Biology and Medicine, 145, 105449. https://doi.org/10.1016/j.compbiomed.2022.105449
Authors:
Richard Rios
Robert J.H. Miller
Nipun Manral
Tali Sharir
Andrew J. Einstein
Mathews B. Fish
Terrence D. Ruddy
Philipp A. Kaufmann
Albert J. Sinusas
Edward J. Miller
Timothy M. Bateman
Sharmila Dorbala
Marcelo Di Carli
Serge D. Van Kriekinge
Paul B. Kavanagh
Tejas Parekh
Joanna X. Liang
Damini Dey
Daniel S. Berman
Piotr J. Slomka
Affiliated Authors:
Andrew J. Einstein
Subjects:
Author Keywords:
machine learning
clinical implementation
missing values
prognosis
myocardial perfusion imaging
Publication Type:
Article
Unique ID:
10.1016/j.compbiomed.2022.105449
PMID:
Publication Date:
Data Source:
Scopus

Record Created: